Box plot of matplotlib visualization: plt.boxplot()

Function function: reflect the abnormal situation of the data; it is mainly used to analyze the internal distribution state or dispersion state of the data, including upper and lower limits, quantiles, and outliers;

调用方法：plt.boxplot(x, notch=None, sym=None, vert=None, whis=None, positions=None, widths=None, patch_artist=None, meanline=None, showmeans=None, showcaps=None, showbox=None, showfliers=None, boxprops=None, labels=None, flierprops=None, medianprops=None, meanprops=None, capprops=None, whiskerprops=None)

Parameter Description:

x: Specify the data to draw the boxplot;

notch: Whether to display the boxplot in the form of a notch, the default is not notch;

sym: Specifies the shape of the abnormal point, the default is 'o';

vert: Whether to place the boxplot vertically, the default is to place vertically;

whis: Specify the distance between the upper and lower whiskers and the upper and lower quartiles, the default is 1.5 times the quartile difference;

positions: Specify the position of the boxplot, the default is [0,1,2…];

widths: Specify the width of the boxplot, the default is 0.5;

patch_artist: Whether to fill the color of the box;

meanline: Whether to represent the mean in the form of a line, and the default is to represent it in points;

showmeans: Whether to display the mean value or not by default;

showcaps: Whether to display the two lines at the top and end of the boxplot, which are displayed by default;

showbox: Whether to display the box of the box plot, the default display;

showfliers: whether to display abnormal values, the default display;

boxprops: Set the properties of the box, such as border color, fill color, etc.;

boxprops = {'color':'g', 'facecolor':'yellow'}

'color' : 'g' the color of the box border

'facecolor' : 'yellow' box fill color

labels: Add labels to the boxplot, similar to the role of the legend;

flierprops: Set the properties of outliers, such as the shape, size, fill color, etc. of outliers;

medianprops: Set the properties of the median, such as line type, thickness, etc.;

meanprops: Set the properties of the mean, such as point size, color, etc.;

capprops: Set the properties of the top and end lines of the boxplot, such as color, thickness, etc.;

whiskerprops: Set whisker properties, such as color, thickness, line type, etc.;

Draw a boxplot:

#利用numpy库生成100个服从标准正态分布随机数
x = np.random.normal(0,1,100)

plt.boxplot(x,  # 指定绘图数据
           notch = True,sym = 'o' , # 凹凸形状
           patch_artist = True,     # 要求用自定义颜色填充盒形图，默认白色填充
           showmeans = True,        # 以点的形式显示均值
           boxprops = {'color':'black', 'facecolor':'#9999ff'},  # 设置箱体属性，填充色和边框色
           flierprops = {'marker':'o', 'markerfacecolor':'red', 'color':'black'}, # 设置异常值属性，点的形状、填充色和边框色
           meanprops = {'marker':'o', 'markerfacecolor':'c',},   # 设置均值点的属性，点的形状、填充色
           medianprops = {'linestyle':'--', 'color':'orange'})   # 设置中位数线的属性，线的类型和颜色
            

# 去除箱线图的上边框与右边框的刻度标签
plt.tick_params(top = 'off', right = 'off')

plt.show()

Draw multiple sets of boxplots: observe the distribution and outliers of multiple sets of data (or features) at the same time

#利用 numpy库生成三组正态分布随机数
x = [np.random.normal(0,std,100) for std in range(1,4)]

# 绘图
plt.boxplot(x, 
            patch_artist = True,sym = 'o',
            labels = ['一组','二组','三组'], # 添加具体的标签名称
            showmeans=True, 
            boxprops = {'color':'black','facecolor':'#9999ff'}, 
            flierprops = {'marker':'o','markerfacecolor':'red','color':'black'},
            meanprops = {'marker':'D','markerfacecolor':'indianred','color' : 'y',},
            medianprops = {'linestyle':'--','color':'orange'})

# 显示图形

plt.show()

Box plot of matplotlib visualization: plt.boxplot()

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